Integration of Surface Reflectance and Aerosol Retrieval Algorithms for Multi‐Resolution Aerosol Optical Depth Retrievals over Urban Areas.

The SEMARA approach, an integration of the Simplified and Robust Surface Reflectance
Estimation (SREM) and Simplified Aerosol Retrieval Algorithm (SARA) methods, was used to
retrieve aerosol optical depth (AOD) at 550 nm from a Landsat 8 Operational Land Imager (OLI)
at 30 m spatial resolution, a Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) at
500 m resolution, and a Visible Infrared Imaging Radiometer Suite (VIIRS) at 750 m resolution over
bright urban surfaces in Beijing. The SEMARA approach coupled (1) the SREM method that is used
to estimate the surface reflectance, which does not require information about water vapor, ozone,
and aerosol, and (2) the SARA algorithm, which uses the surface reflectance estimated by SREM
and AOD measurements obtained from the Aerosol Robotic NETwork (AERONET) site (or other
high-quality AOD) as the input to estimate AOD without prior information on the aerosol optical
and microphysical properties usually obtained from a look-up table constructed from long-term
AERONET data. In the present study, AOD measurements were obtained from the Beijing AERONET
site. The SEMARA AOD retrievals were validated against AOD measurements obtained from two
other AERONET sites located at urban locations in Beijing, i.e., Beijing_RADI and Beijing_CAMS,
over bright surfaces. The accuracy and uncertainties/errors in the AOD retrievals were assessed
using Pearson’s correlation coefficient (r), root mean squared error (RMSE), relative mean bias (RMB),
and expected error (EE = ± 0.05 ± 20%). EE is the envelope encompassing both absolute and relative
errors and contains 68% (±1σ) of the good quality retrievals based on global validation. Here, the EE
of the MODIS Dark Target algorithm at 3 km resolution is used to report the good quality SEMARA
AOD retrievals. The validation results show that AOD from SEMARA correlates well with AERONET
AOD measurements with high correlation coefficients (r) of 0.988, 0.980, and 0.981; small RMSE of
0.08, 0.09, and 0.08; and small RMB of 4.33%, 1.28%, and −0.54%. High percentages of retrievals, i.e., 
85.71%, 91.53%, and 90.16%, were within the EE for Landsat 8 OLI, MODIS, and VIIRS, respectively.
The results suggest that the SEMARA approach is capable of retrieving AOD over urban areas with
high accuracy and small errors using high to medium spatial resolution satellite remote sensing
data. This approach can be used for aerosol monitoring over bright urban surfaces such as in Beijing,
which is frequently affected by severe dust storms and haze pollution, to evaluate their effects on
public health.